# Automation & Off-chain Data

## The Problem

In the realm of blockchain development, especially with decentralized applications (dApps), a significant challenge emerges in the form of limited auto-execution capabilities. Traditionally, smart contracts, despite their advanced functionalities, lack the inherent ability to initiate or call methods automatically. This limitation poses a hurdle in the seamless operation and scalability of blockchain applications.

## The Solution

To address this gap, automation solutions have been developed. These systems are designed to monitor both on-chain and off-chain data sources continuously. They are programmed to recognize specific predefined conditions. Once these conditions are met, the automation system springs into action, executing the necessary transactions without human intervention.

## Use cases

1. Auto Harvesting in DeFi: In decentralized finance applications, automation can manage yield farming strategies, harvesting rewards automatically when they reach a certain threshold, thereby optimizing the return on investment for users.
2. Limit Orders in Trading: Automated systems can execute trades when certain price points are hit, mirroring the functionality of limit orders in traditional trading but within a decentralized environment.

Read more about Gelato Web3 functions below!

<table data-view="cards"><thead><tr><th data-type="content-ref"></th><th></th></tr></thead><tbody><tr><td><a href="/pages/QYfDY9mxXNcCJi1mPXQZ">/pages/QYfDY9mxXNcCJi1mPXQZ</a></td><td><span data-gb-custom-inline data-tag="emoji" data-code="1f4da">📚</span> Gelato Web3 Functions</td></tr></tbody></table>


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://devdocs.educhain.xyz/services/automation-and-off-chain-data.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.